IDENTIFICATIONANDCONTROL OF NONLINEAR SYSTEMS USING MULTIPLE GENERALIZED PREDICTIVE CONTROL BASED NEURO-FUZZY MODEL

NGUYEN , TUAN HUNG (2014) IDENTIFICATIONANDCONTROL OF NONLINEAR SYSTEMS USING MULTIPLE GENERALIZED PREDICTIVE CONTROL BASED NEURO-FUZZY MODEL. Masters thesis, Universiti Teknologi PETRONAS.

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2014-ELECTRIC-IDENTIFICATION AND CONTROL OF NONLINEAR SYSTEMS USING MULTIPLE GENERALIZED PREDICTIVE CONTROL BASED NEURO-FUZZY MODEL-NGUYEN TUAN HUNG.pdf
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Abstract

This thesis presents an approach of identification and control of nonlinear
processes by using Multiple Generalized Predictive Control (MGPC) based Neurofuzzy
model. Firstly, the dynamic characteristics of a nonlinear system is identified by
a Neuro-fuzzy model which is formulated as an alternative form as multiple linear
Auto-Regressive Exogenous (ARX) sub models. Subsequently, the MGPC are
designed in which each GPC is based on the sub ARX model working cooperatively
with other GPCsto control the nonlinearsystem.

Item Type: Thesis (Masters)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE: Engineering > Electrical and Electronic
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 16 Sep 2021 12:37
Last Modified: 16 Sep 2021 12:37
URI: http://utpedia.utp.edu.my/id/eprint/21219

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